# High-precision NLI

Natural language inference model supporting 100 languages, suitable for multilingual zero-shot classification tasks

A zero-shot text classification model based on DeBERTa-v3-base, used to determine the logical relationship (entailment, neutral, or contradiction) between premises and hypotheses.

DeBERTa-v3-large model optimized for zero-shot classification tasks, supporting text classification without training data

A RoBERTa-large model designed for efficient zero-shot classification, trained on commercially friendly data, capable of performing text classification tasks without training data.

A DeBERTa-v3-large model specifically designed for efficient zero-shot classification, trained on fully commercially friendly synthetic data and NLI datasets, supporting GPU/CPU inference

A text entailment model fine-tuned based on DeBERTa-v3-large, used to judge the entailment relationship between texts

Natural language inference model supporting 100 languages, suitable for multilingual zero-shot classification tasks

A zero-shot classification natural language inference model supporting Danish, Norwegian, and Swedish

Multilingual natural language inference model based on mDeBERTa-v3-base, supporting zero-shot classification in 100 languages

Roberta-large model trained on the MNLI dataset for natural language inference tasks.

A natural language inference model based on the DeBERTa-v3-large architecture, trained on SNLI and MultiNLI datasets for determining the relationship between sentence pairs.

This model is a natural language inference model fine-tuned on the PAWS-X-fr dataset based on Camembert-base, specifically designed for French text paraphrase identification tasks.

This is a text classification model based on the bert-base-uncased pre-trained model and fine-tuned on the MultiNLI dataset

DeBERTa-v3-large model trained on MultiNLI dataset for textual entailment relationship judgment

A cross-encoder model based on microsoft/deberta-v3-base, trained for natural language inference tasks, capable of determining the relationship between sentence pairs (contradiction, entailment, or neutral).

DeBERTa-v3 XL is a large-scale pre-trained language model based on the Transformer architecture, specifically fine-tuned for natural language inference tasks.

A fine-tuned version based on the xlm-roberta-large-en-ru model on the MNLI dataset, supporting natural language inference tasks in English and Russian.

MNLI task model fine-tuned on DeBERTa-v3-large, achieving 91.75% accuracy on the GLUE MNLI evaluation set

DeBERTa-v3 model trained on MultiNLI, Fever-NLI, and ANLI datasets, excelling in zero-shot classification and natural language inference tasks

A multilingual natural language inference model supporting 100 languages, suitable for zero-shot classification tasks